title: Cross-sectional study: Does combining optical coherence tomography measurements using the 'Random Forest' decision tree classifier improve the prediction of the presence of perimetric deterioration in glaucoma suspects?
abstract: OBJECTIVE
  To develop a classifier to predict the presence of visual field (VF) deterioration in glaucoma suspects based on optical coherence tomography (OCT) measurements using the machine learning method known as the 'Random Forest' algorithm.
  
  
  METHODS
  Case-control study.
  
  
  METHODS
  293 eyes of 179 participants with open angle glaucoma (OAG) or suspected OAG.
  
  
  METHODS
  Spectral domain OCT (Topcon 3D OCT-2000) and perimetry (Humphrey Field Analyser, 24-2 or 30-2 SITA standard) measurements were conducted in all of the participants. VF damage (Ocular Hypertension Treatment Study criteria (2002)) was used as a 'gold-standard' to classify glaucomatous eyes. The 'Random Forest' method was then used to analyse the relationship between the presence/absence of glaucomatous VF damage and the following variables: age, gender, right or left eye, axial length plus 237 different OCT measurements.
  
  
  METHODS
  The area under the receiver operating characteristic curve (AROC) was then derived using the probability of glaucoma as suggested by the proportion of votes in the Random Forest classifier. For comparison, five AROCs were derived based on: (1) macular retinal nerve fibre layer (m-RNFL) alone; (2) circumpapillary (cp-RNFL) alone; (3) ganglion cell layer and inner plexiform layer (GCL+IPL) alone; (4) rim area alone and (5) a decision tree method using the same variables as the Random Forest algorithm.
  
  
  RESULTS
  The AROC from the combined Random Forest classifier (0.90) was significantly larger than the AROCs based on individual measurements of m-RNFL (0.86), cp-RNFL (0.77), GCL+IPL (0.80), rim area (0.78) and the decision tree method (0.75; p<0.05).
  
  
  CONCLUSIONS
  Evaluating OCT measurements using the Random Forest method provides an accurate prediction of the presence of perimetric deterioration in glaucoma suspects.
authors.affiliation: Department of Ophthalmology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
authors.forename: Koichiro
authors.initials: K
authors.lastname: Sugimoto
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Murata
authors.forename: Hiroyo
authors.initials: H
authors.lastname: Hirasawa
authors.forename: Makoto
authors.initials: M
authors.lastname: Aihara
authors.forename: Chihiro
authors.initials: C
authors.lastname: Mayama
authors.forename: Ryo
authors.initials: R
authors.lastname: Asaoka
keywords: Optical Coherence Tomography; Random Forest; Visual Field